2009
DOI: 10.1057/palgrave.jors.2602638
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Measuring the performance of nations at the Olympic Games using DEA models with different preferences

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Cited by 48 publications
(23 citation statements)
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“…In the standard DEA models like CCR and BCC, the classic Pareto preference is assumed, as in this work. However, we emphasize there are many real applications where different preferences are indeed useful, see Liu et al (2006) and Zhang et al (2009) for some examples. Let X = (x 1 , .…”
Section: Disposability Assumptions In Deamentioning
confidence: 99%
“…In the standard DEA models like CCR and BCC, the classic Pareto preference is assumed, as in this work. However, we emphasize there are many real applications where different preferences are indeed useful, see Liu et al (2006) and Zhang et al (2009) for some examples. Let X = (x 1 , .…”
Section: Disposability Assumptions In Deamentioning
confidence: 99%
“…CHURILOV; FLITMAN, 2006;HAI, 2007;LEI et al, 2014;LI et al, 2008LI et al, , 2015LINS et al, 2003;LOZANO et al, 2002;MARINHO;ALMEIDA;CARDOSO, 2016;; SOARES DE MELLO; ANGULO-MEZA; BRANCO DA SILVA, 2008; SOARES DE MELLO; LACERDA, 2012;WU, H. et al, 2013;CHEN, 2009;ZHOU;YANG et al, 2009;ZHANG, D. et al, 2009 Índices h sucessivos também podem ser calculados para diversos fins. Prathap (2006) propôs o cálculo do índice h do índice h de autores, para encontrar os principais autores de certo departamento, enquanto Schubert (2007) calculou índices h sucessivos de acordo com níveis distintos de agregação.…”
Section: Introductionunclassified
“…Li, Liang, Chen, and Morita (2008) assumed that different nations impose different AR constraints and applied context-dependent AR DEA to measuring the performance of participating nations. Zhang, Li, Meng, and Liu (2009) discussed underlying preferences in DEA and proposed DEA models with lexicographic preference to measure performance. Wu, Liang, and Yang (2009b) used a cross-efficiency DEA model to effectively rank participating nations and incorporated cluster analysis to effectively set frontier targets for inefficient DMUs.…”
Section: Introductionmentioning
confidence: 99%